Hemiplegia and hemiparesis may be caused by various illnesses, including Parkinson's disease, multiple sclerosis, spinal cord injury, traumatic brain injury, cerebral palsy, poliomyelitis, and arthritis. In addition, over eight hundred thousand Americans suffer a stroke every year, leaving many hemiplegic or hemiparetic. Damage suffered in one side of the brain often causes disability to limbs on the opposite side. An increasing population of stroke survivors, and others, are facing enormous difficulties in performing daily chores, and many require assistance from others. The cost of care for stroke survivors, including lost productivity and premature mortality, is enormous.
In many cases, rehabilitation training remains the sole therapeutic approach to recover lost motor skills. The majority of stroke patients who initiate rehabilitation therapy soon after a stroke are able to regain a significant amount of motor function. In some examples, a recovery of motor function at the shoulder is achieved in two to three weeks, and a recovery of motor function at the elbow is achieved in six to eight weeks. However, recovery of motor function at the wrist and fingers is more difficult. For patients who start their training in a later stage of disability, the recovery of lost function is often limited, resulting in chronic hemiplegia or hemiparesis. As the benefits of treatment begin to fade, rehabilitation therapy is ultimately terminated. Patients who are left hemiplegic or hemiparetic are often placed at skilled nursing facilities, rather than returning home.
Wearable robots have been studied for rehabilitation and assistance of those suffering from disability. In some examples, prosthetic devices substitute lost biological limbs with mechanical proxies. Prosthetic devices improve the quality of life of amputees, but they are not applicable to hemiplegic and hemiparetic patients whose impaired arms and hands are still physically attached to their body. In other examples, exoskeleton devices extend strength and endurance by attaching actuators to individual human joints. Orthotic exoskeletons may help restore lost limb functions, but most are developed for patients with lower extremity disabilities. The few devices designed to aid the weakened hand are highly complex, bulky, uncomfortable, and limited in performance. These include a pneumatically actuated device that is controlled by electromyography (EMG) to achieve pinching actions described by M. DiCicco, et al., “Comparison of control strategies for an EMG controlled orthotic exoskeleton for the hand,” in Proc. of IEEE International Conference on Robotics and Automation (ICRA), New Orleans, La., 2004, pp. 1622-1627; tendon-driven rigid frames that monitor head motion to perform pouring tasks described by Y. Hasegawa, et al., “Wearable handling support system for paralyzed patient,” in Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2008, pp. 741-746; and a frameless device with a modified differential mechanism activated by wrist movement to tighten a grip described by K. In, et al., “Investigation of friction characteristics of a tendon driven wearable robotic hand,” in Proc. of International Conference on Control Automation and Systems (ICCAS), October 2010, pp. 568-573.
More often, upper limb exoskeleton devices are employed for robot-assisted rehabilitation treatment. These therapies have been shown to increase motor recovery in patients suffering from 1) subacute and chronic stroke as described by P. F. M. Sale, et al., “Effects of upper limb robot-assisted therapy on motor recovery in subacute stroke patients,” J Neuroeng Rehabil., vol. 11, no. 104, pp. 111-121, 2014 and S. Mazzoleni, et al., “Robot-aided therapy on the upper limb of subacute and chronic stroke patients: A biomechanical approach,” in Proc. of IEEE International Conference on Rehabilitation Robotics (ICORR), Zurich, Switzerland, 2011, 2) subacute cervical spinal cord injury described by J. Zariffa, et al., “Effect of a robotic rehabilitation device on upper limb function in a sub-acute cervical spinal cord injury population,” in Proc. of IEEE International Conference on Rehabilitation Robotics (ICORR), Zurich, Switzerland, 2011, and 3) multiple sclerosis described by A. Basteris, et al., “A tailored exercise of manipulation of virtual tools to treat upper limb impairment in Multiple Sclerosis,” in Proc. of IEEE International Conference on Rehabilitation Robotics (ICORR), Zurich, Switzerland, 2011.
While exoskeleton devices show great promise for rehabilitation training, they are not applicable to assisting hemiplegic patients at home. For example, the application of an external force or torque to an affected finger may be dangerous unless it is executed under supervision of a professional. In many cases, the disabled fingers have severely limited tactile function or are completely numb. With limited sensitivity, a patient may be unaware that an externally applied force or torque is damaging their disabled finger.
Despite advances in the design and control of wearable robots, neither prosthetic devices nor exoskeleton devices meet the requirements for assisting chronic hemiplegic or hemiparetic patients at home.
In another example, supernumerary robotic (SR) limbs are attached to the body to assist a patient to hold objects, support body weight, and streamline task execution described by B. Llorens-Bonilla, et al., “Demonstration-based control of supernumerary robotic limbs,” in Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vilamoura, Portugal, 2012, pp. 3936-3942; C. Davenport, et al., “Design and Biomechanical Analysis of Supernumerary Robotic Limbs,” in Proc. of ASME Dynamic Systems and Control Conference (DSCC), Fort Lauderdale, Fla., 2012; B. Llorens—Bonilla and H. Asada, “Control and Coordination of Supernumerary Robotic Limbs based on Human Motion Detection and task Petri Net,” in Proc. of ASME Dynamic Systems and Control Conference (DSCC), Palo Alto, Calif., 2013; F. Parietti and H. Asada, “Dynamic Analysis and State Estimation for Wearable Robotic Limbs Subject to Human-Induced Disturbances,” in Proc. of IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, May 2013; B. Llorens—Bonilla and H. Asada, “A Robot on the Shoulder: Coordinated Human-Wearable Robot Control using Coloured Petri Nets and Partial Least Squares Predictions,” in Proc. IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, May 2014; F. Parietti and H. Asada, “Supernumerary Robotic Limbs for Aircraft Fuselage Assembly: Body Stabilization and Guidance by Bracing,” in Proc. of IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, May 2014; F. Parietti and H. Asada, “Bracing the Human Body with Supernumerary Robotic Limbs for Physical Assistance and Load Reduction,” in Proc. of IEEE International Conference on Robotics and Automation, (ICRA), Hong Kong, China, May 2014; F. Y. Wu and H. Asada, “Bio-Artificial Synergies for Grasp Control of Supernumerary Robotic Fingers,” in Robotics: Science and Systems X (RSS), Berkeley, Calif., 2014; and F. Y. Wu and H. Asada, “Supernumerary Robotic Fingers: an Alternative Upper Limb Prosthesis,” in Proc. of ASME Dynamic Systems and Control Conference (DSCC), San Antonio, Tex., 2014.
In one example, a set of wrist-mounted supernumerary robotic (SR) fingers attached to a functional hand augments the functionality of the same functional hand to perform tasks that typically require two hands. This may be applicable to hemiparetic or hemiplegic patients left with a single functional hand.
SR fingers have some advantages. For example, no torque is applied to a disabled human finger, and the SR fingers can safely generate a large force. Unlike exoskeleton devices, SR Fingers are not constrained to affected, disabled fingers. SR fingers can assume an arbitrary posture that is independent of the affected fingers. This allows an SR finger to assist in the performance of daily tasks that are difficult to perform with a finger exoskeleton. A SR finger can touch a hot object that would otherwise burn affected, insensitive fingers. In contrast, a finger exoskeleton device would force the insensitive, affected fingers to grasp the hot object directly.
Unfortunately, the SR fingers described with reference to the articles mentioned hereinbefore are mechanically complex. In addition, the human-robot communication techniques are highly sophisticated and require complex user training. An instrumented glove is utilized to measure the hand gestures that form the basis for control of the SR fingers. A number of hand gesture measurement products have been developed, including a finger mount glove for computer input applications (e.g., the Gest wearable device) and numerous sensory gloves for operating robots or machines. Most of these gloves are built with sophisticated sensors and complex integrated circuits that measure movement, orientation, and configuration of the hand. For applications that only require a simple interpretation of hand gesture, e.g., opening or closing of the hand, these gloves are too costly. In addition, the user of the wearable glove cannot use their hands to perform regular tasks, e.g., picking up small items and washing hands, while wearing the glove. For at least these reasons, the wearable gloves and SR fingers described with reference to the aforementioned articles are unsuitable for general home use applications.
In summary, improvements in wearable hand gesture sensors and in the design and control of wearable robotic devices are desired to provide rehabilitation and assistance to people suffering from chronic hemiplegic or hemiparetic disabilities.